Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

A cell means analysis of mixed linear models

The purpose of this paper is to describe a simple procedure for the estima-tion of parameters in the unbalanced mixed linear model. There are implications for hypothesis testing and interval estimation, A feature of these estimators is that they are expressed in terms of simple formulas. This has obvious advantages for computations and small sample analysis. In addition, the formulas suggest useful diagnostic procedures for assessing the quality of the data as well as possible defects in the model assumptions. The concepts are illustrated with several examples. Evidence is presented to indicate that, in cases of modest imbalance, these estimators are highly efficient and dominate AOV estimates over most of the parameter space. In cases of more extreme imbalance, the results are qualitatively the same but the estimators are less efficient than the AOV estimators for small values of the parameters. The extension of this method to factorial models with missing cells is not complete.     

Development of an integrated information management model: A case of textile industry

For past two decades many organisations have tried to implement integrated information management systems for better production management based on co-ordination of information and therefore activities of different departments. Although Enterprise Resource Planning systems have been in the market for the past decade, many industries find it difficult to implement such systems due to the amount of work involved in streamlining the documentation, customisation and of high costs reported in implementation. An attempt is made through this paper to propose an integrated model, which can be easily understood by production personnel, with specific emphasis on the textile sector.     

Multi-objectives exception management model for semiconductor back-end environment under turnkey service

On-time delivery is the need for customer satisfaction which is a critical factor in the survival of the semiconductor industry. The on-time-delivery performance of the whole semiconductor turnkey service depends on the performance of the back-end factories. Unfortunately, undesirable and inevitable production variations make it difficult to maintain and improve a factory's performance and more objectives such as cycle time, throughput rate and the due-date accuracy need to be simultaneously considered. This paper presents an exception management model in order to compromise the contradicting needs of delivery accuracy, throughput rate and cycle time. The exception model can be divided into three parts: (1) an integrated performance index is proposed to compromise multiple performance measures; (2) an AWDL (available WIP deviation level) determination model is designed to gather proper AWDLs for triggering exceptions and (3) a WIP correction action is proposed to make abnormal WIP levels back to normal levels as soon as possible. To evaluate the proposed WIP exception management model, a simulation model is constructed and experiments are then conducted. The simulation results show that the proposed model helps back-end factories to set proper exception triggering conditions, reduce uncertainty occurrences and achieve better performances on due dates.     

Maximal Invariant and Weakly Equivariant Estimators

Equivariant functions can be useful for constructing of maximal invariant statistic. In this article, we discuss construction of maximal invariants based on a given weakly equivariant function under some additional conditions. The theory easily extends to the case of two or more weakly equivariant functions. Also, we derive a maximal invariant statistic when the group contains a sharply transitive and a characteristic subgroup. Finally, we consider the independence of invariant and weakly equivariant functions under some special conditions.     

Adolescent girls’ race/ethnic status, identities, and drive for thinness

Using data from 7272 adolescent US girls, we explore how girls’ race/ethnic group status affects their bodyweight, perceptions of overweight, and weight control practices. We hypothesize that a girl’s race/ethnic status influences her basic identity which in turn prompts her to adopt or reject a “drive for thinness.” After controlling for family and peer support, school engagement, family SES, maturation, and family structure, we find that girls’ race/ethnic status influences their susceptibility to the thinness ideals of mainstream culture. African American girls weigh more than Asian, Hispanic, or White girls, but at any given weight they perceive themselves as overweight and attempt to control their weight less. Asian American and White girls invest most in thinness dynamics. Some evidence also suggests girls from lower SES families are less driven to be thin. Our results affirm the utility of viewing material bodies as “situations” that are experienced and interpreted in accord with identity group relations and dynamics.     

Measuring the Influence of Unemployment Insurance on Unemployment Experiences

This article investigates the comprehensive effects of unemployment insurance (UI) policies on the amount of time and unemployment that individuals report between jobs. The econometric model jointly determines the effects of UI on the lengths of nonemployment spells, the classification of these spells as unemployment, and the likelihood of collecting program benefits. The model carefully attempts to isolate variation in UI benefits attributable to differences in generosity across programs to avoid biases in estimating policy effects induced by other contaminating sources of benefit variation. Using data on men from the National Longitudinal Survey of Youth, the empirical results find (a) UI recipients typically experience longer spells between jobs, at least up to the exhaustion of UI benefits, and report substantially larger fractions of these spells as unemployment; (b) weekly benefit amounts exert no significant influence on the likelihood of UI recipiency, on the length of spells between jobs, or on the fraction of these spells classified as unemployment; and (c) increases in weeks of UI eligibility raise the likelihood of UI collection and lengthen the number of weeks of unemployment between jobs by inducing long spells to become longer and not by altering short-duration behavior.     

Graphical methods for comparing confounding in two or more designs

In many circumstances it is necessary to design an experiment with partial confounding of parameter estimates. In this situation, one would like to have tools to assess and compare candidate designs graphically. In this paper we discuss two graphical representations of design properties, and illustrate their application with two examples.     

Management of Allergic Respiratory Disease by the Nurse Practitioner

The results of several studies have established the validity of the SCOFF questionnaire (a 5-question screening tool for eating disorders), but researchers need to explore further replicability using the US version in the graduate school population. In this study, the authors asked 335 graduate students attending the Northwestern student health clinic on the Chicago campus to complete a written survey anonymously. A total of 305 (91%) patients completed the survey. The sensitivity and specificity for the SCOFF was 53.3% and 93.2%, respectively. This produced a PPV (the proportion who tested positive on the screen and actually had an eating disorder) of 66.7% and an NPV (the proportion of those who tested negative on the screen and actually did not have an eating disorder) of 88.7%. More than 80% of respondents were dissatisfied with their shape and weight, with over one third having a moderate to severe body image disturbance. The SCOFF is an easy instrument to administer that health care providers can use to screen for eating disorders in the primary care setting.